Civil and mechanical engineering projects, GIS (Geographical Information Systems) mapping programs, military simulations, and numerous other applications all require accurate three dimensional (3D) computer models of real-world objects.
Most previous methods for creating 3D models involve extensive manual measurement and modeling. The measuring component may be achieved either through direct measurement (such as surveying) of the objects themselves or through measuring images of the objects using the science of photogrammetry. The modeling component typically involves manually inputting the measurements into computer modeling programs such as computer-aided design (CAD) software, GIS, or other similar solid modeling packages. This process is labor intensive and error prone.
Point cloud capture technology, such as laser scanning or automated photogrammetric stereo matching, is a relatively new technology for improving upon this 3D-modeling process. These systems scan objects or scenes to construct a “point cloud” consisting of many 3D point measurements of the scene. These points can then be used to guide the process of feature extraction.
Many companies need 3D virtual models of the piping, structural steel, ducting, and other critical elements within their industrial facilities, and it has become accepted practice to scan these facilities and create these 3D models using the resulting point cloud data. Towards this end, multiple software applications have been developed to enable manual, semi-automated, and fully-automated extraction of extruded objects to assist in the modeling of pipe networks, structural steel, and other common features. Fully-automated extraction is the most desirable approach for obvious reasons of cost savings. However, automated algorithms for extracting objects of extrusion from point cloud data can produce “false positives”—extracted objects that are not correct. For example, rounded edges on corners will result in a false positive for many naive automated cylinder extraction routines that simply test the mathematical fit of a cylinder to the scanned surface points. False positives typically need to be manually detected and removed from a model before it is finalized, thereby increasing costs.
It would therefore be desirable to develop a system, a method, and an apparatus able to automatically detect and delete erroneously extracted objects of extrusion.